A batch process is performed on mass data such as a daily or monthly process of finance and account records. In this batch process, it is important to guarantee a finish time. This is because, if the batch process does not finish, the start of a subsequent business service is disrupted. Therefore, the batch process requires high-speed for finishing even mass data in a predetermined time, reliability for a reliable finish, and rapid handling of failures. In addition, the batch process is also required to have a low costs and facilitated operations which are necessary to reduce Total Cost of Ownership (TCO).
In relation to these matters, for example, PTL 1 discloses a method (job scheduling method) of controlling a job net (also referred to as a job network) in which a plurality of batch jobs are correlated with each other in order to intensively control a lot of jobs and to easily monitor execution circumstances of jobs.
On the other hand, the job net is required to finish in a predetermined time in order to start a service which uses an execution result of the job net at a predetermined start time. However, since a process time of the batch job depends on an amount of data which is input and output, the job net cannot finish in a predetermined time if data increases. As a countermeasure for this, for example, PTL 2 discloses a job scheduling method in which data is divided, the divided data is assigned to each job so as to be processed in parallel on a plurality of computers, thereby speeding up a batch job process of mass data. In the job scheduling method of PTL 2, data is divided in advance, job definitions corresponding to the number of divisions are generated, and a relationship between the divided data and the job definition is recorded in a parallel process management table. A job which is to be executed is determined by referring to the parallel process management table when scheduling is performed, and a job definition including identification data of the job is provided to job management.